A computer-implemented method for suppressing noise from audio signal uses both statistical noise estimation and neural network noise estimation to achieve more desirable noise reduction. The method is performed by a noise suppression computer software application running on an electronic device. The noise suppression computer software application first transforms the speech signal in time domain into frequency domain before determining a statistical noise estimate and a neural network noise estimate. The noise suppression computer software application merges the two noise estimates to derive a final noise estimate, and determines and refines a noise suppression filter. The filter is applied to the speech signal in frequency domain to obtain an enhanced signal. The enhanced signal is transformed back into time domain.
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3. The method of claim 2 wherein said set of speech features includes at least one of a signal classification feature, a speech/noise log likelihood ratio, a post signal to noise ratio, and a prior signal to noise ratio.
4. The method of claim 1 wherein said neural network is Recurrent Neural Network (RNN).
5. The method of claim 1 wherein said statistically estimated noise is obtained using a time recursive average formula.
6. The method of claim 1 wherein said noise suppression computer software application merges said statistically estimated noise and said neural network estimated noise using a maximum operator.
7. The method of claim 1 wherein said gain filter is a log Minimum Mean-Square Error filter.
8. The method of claim 1 wherein said gain filter is refined using a smoothing process before said gain filter is applied to said frequency domain signal.
9. The method of claim 1 wherein analyzing said audio input signal comprises buffering audio samples of said audio input signal, windowing said buffered audio input signal and transforming said windowed audio samples into said frequency domain signal.
10. The method of claim 9 wherein windowing said buffered audio input signal includes multiplying said buffered audio input signal by a hamming or sine waveform, and transforming said windowed audio samples includes a discrete Fourier transformation.
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May 24, 2022
November 26, 2024
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